U.S. patent application number 14/562941 was filed with the patent office on 2016-06-09 for systems and methods for categorizing, evaluating, and displaying user input with publishing content.
The applicant listed for this patent is AOL Inc.. Invention is credited to Jeffrey Todd WILSON.
Application Number | 20160162500 14/562941 |
Document ID | / |
Family ID | 56094500 |
Filed Date | 2016-06-09 |
United States Patent
Application |
20160162500 |
Kind Code |
A1 |
WILSON; Jeffrey Todd |
June 9, 2016 |
SYSTEMS AND METHODS FOR CATEGORIZING, EVALUATING, AND DISPLAYING
USER INPUT WITH PUBLISHING CONTENT
Abstract
Systems and methods are provided for displaying received
publishing content on a web page along with one or more user
elements by which one or more users may submit sentiment input or
textual input in relation to the received publishing content or a
subportion of the received publishing content; receiving a user
input related to the displayed publishing content displayed on the
web page, the user input including an identification of a
subportion of the displayed publishing content and a sentiment
input or a textual input; analyzing any user input received from
each of one or more of the plurality of users in relation to the
subportion; computing a sentiment score based on analysis of the
analyzed user inputs received from each of one or more of the
plurality of users in relation to the subportion; and displaying
indicia representing the sentiment score computed for the
subportion.
Inventors: |
WILSON; Jeffrey Todd;
(Ashburn, VA) |
|
Applicant: |
Name |
City |
State |
Country |
Type |
AOL Inc. |
Dulles |
VA |
US |
|
|
Family ID: |
56094500 |
Appl. No.: |
14/562941 |
Filed: |
December 8, 2014 |
Current U.S.
Class: |
715/234 |
Current CPC
Class: |
G06F 16/958 20190101;
G06Q 50/01 20130101; G06Q 30/02 20130101 |
International
Class: |
G06F 17/30 20060101
G06F017/30; G06F 3/0482 20060101 G06F003/0482; G06F 3/0484 20060101
G06F003/0484 |
Claims
1. A computer-implemented method for evaluating user input relating
to electronic published content, the method comprising: receiving,
over an electronic network, electronic publishing content for
display online; displaying the received publishing content on a web
page along with one or more user elements by which one or more
users may submit sentiment input or textual input in relation to
the received publishing content or a subportion of the received
publishing content; receiving, from each of a plurality of users, a
user input related to the displayed publishing content displayed on
the web page, the user input including an identification of a
subportion of the displayed publishing content and a sentiment
input or a textual input; analyzing, for each subportion of the
displayed publishing content, any user input received from each of
one or more of the plurality of users in relation to the
subportion; computing, for each subportion of the displayed
publishing content, a sentiment score based on analysis of the
analyzed user inputs received from each of one or more of the
plurality of users in relation to the subportion; and displaying,
for each subportion of the displayed publishing content, indicia
representing the sentiment score computed for the subportion, along
with at least one user element by which one or more further users
are enabled to provide user input to further modify the computed
and indicated sentiment score.
2. The computer-implemented method of claim 1, wherein the textual
input is a user comment.
3. The computer-implemented method of claim 1, wherein the user
input further comprises one or more tags received from the user in
relation to one or more subportions of the publishing content.
4. The computer-implemented method of claim 1, wherein the user
input is a sentiment input or a textual input.
5. The method of claim 1, further comprising: dividing the received
electronic publishing content into a plurality of subportions.
6. The computer-implemented method of claim 1, wherein the
sentiment score is associated with at least one of the plurality of
subportions.
7. The computer-implemented method of claim 4, further comprising:
changing an indicator associated with the at least one subportion
based on the modified sentiment score.
8. A computer system for evaluating user input relating to
electronic published content, the system comprising: a memory
device storing instructions for evaluating user input; and a
processor configured to execute the instructions to perform a
method of: receiving, over an electronic network, electronic
publishing content for display online; displaying the received
publishing content on a web page along with one or more user
elements by which one or more users may submit sentiment input or
textual input in relation to the received publishing content or a
subportion of the received publishing content; receiving, from each
of a plurality of users, a user input related to the displayed
publishing content displayed on the web page, the user input
including an identification of a subportion of the displayed
publishing content and a sentiment input or a textual input;
analyzing, for each subportion of the displayed publishing content,
any user input received from each of one or more of the plurality
of users in relation to the subportion; computing, for each
subportion of the displayed publishing content, a sentiment score
based on analysis of the analyzed user inputs received from each of
one or more of the plurality of users in relation to the
subportion; and displaying, for each subportion of the displayed
publishing content, indicia representing the sentiment score
computed for the subportion, along with at least one user element
by which one or more further users are enabled to provide user
input to further modify the computed and indicated sentiment
score.
9. The computer system of claim 8, wherein the textual input is a
user comment.
10. The computer system of claim 8, wherein the user input further
comprises one or more tags received from the user in relation to
one or more subportions of the publishing content.
11. The computer system of claim 8, wherein the sentiment score is
assigned to one of a sentiment input and a textual input.
12. The computer system of claim 8, further comprising: dividing
the received electronic publishing content into a plurality of
subportions.
13. The computer system of claim 8, wherein the sentiment score is
associated with at least one of the plurality of subportions.
14. The computer system of claim 13, further comprising: changing
an indicator associated with the at least one subportion based on
the modified sentiment score.
15. A non-transitory computer-readable medium storing instructions,
then instructions, when executed by a computer system cause the
computer system to perform a method, the method comprising:
receiving, over an electronic network, electronic publishing
content for display online; displaying the received publishing
content on a web page along with one or more user elements by which
one or more users may submit sentiment input or textual input in
relation to the received publishing content or a subportion of the
received publishing content; receiving, from each of a plurality of
users, a user input related to the displayed publishing content
displayed on the web page, the user input including an
identification of a subportion of the displayed publishing content
and a sentiment input or a textual input; analyzing, for each
subportion of the displayed publishing content, any user input
received from each of one or more of the plurality of users in
relation to the subportion; computing, for each subportion of the
displayed publishing content, a sentiment score based on analysis
of the analyzed user inputs received from each of one or more of
the plurality of users in relation to the subportion; and
displaying, for each subportion of the displayed publishing
content, indicia representing the sentiment score computed for the
subportion, along with at least one user element by which one or
more further users are enabled to provide user input to further
modify the computed and indicated sentiment score.
16. The non-transitory computer-readable medium of claim 15,
wherein the textual input is a user comment.
17. The non-transitory computer-readable medium of claim 15,
wherein the user input further comprises one or more tags received
from the user in relation to one or more subportions of the
publishing content.
18. The non-transitory computer-readable medium of claim 15,
wherein the sentiment score is assigned to one of a sentiment input
and a textual input.
19. The non-transitory computer-readable medium of claim 15,
further comprising: dividing the received electronic publishing
content into a plurality of subportions.
20. The non-transitory computer-readable medium of claim 15,
wherein the sentiment score is associated with at least one of the
plurality of subportions.
Description
TECHNICAL FIELD
[0001] Various embodiments of the present disclosure relate
generally to processing electronic messages, such as over the
Internet. More specifically, particular embodiments of the present
disclosure relate to systems and methods for processing,
evaluating, and displaying user-generated sentiment input and
user-generated comments related to web pages and subportions of web
pages.
BACKGROUND
[0002] Typically, online publishers, such as online media companies
and other publishers of articles, stories, and other electronic
content, provide online web page space and mechanisms for viewers
to comment on, or otherwise interact with, that published content.
Some published content attracts many comments, which may be too
numerous for a reader to easily review and digest. Large sites with
lots of traffic can receive thousands of user comments in relation
to a single popular article. The prevalent way to present comments
related to the articles is to present them together at the end of
the article, which may not be ideal for all readers. Often, the
comments themselves are as interesting as the content, but reading
through all of them to find particular takes or opinions is not
practical.
[0003] In some cases, comments may relate only to one subportion,
e.g., a particular paragraph, sentence, fact, etc., of the article.
Also, specific claims or facts cited in articles may be of special
interest and may spark robust debate, but comments specific to such
points cannot be discerned from general comments about the article.
Because comments are typically displayed in sequential order, it
can be difficult for readers to identify comments related to
specific topics or specific subportions of interest to the reader.
Due to the standard location and scope of comments, comments of
interest to a particular user may be too far down a chain of
comments to appear within a useful distance from the original
content.
[0004] Similarly, some online media companies allow users to rate
or provide other forms of expressing sentiment regarding an article
as a whole, but no ability to express sentiment or view the overall
sentiment related to specific subportions or specific user
comments.
SUMMARY OF THE DISCLOSURE
[0005] According to certain embodiments, computer-implemented
methods are disclosed for evaluating user input relating to
electronic published content. In an exemplary method, the method
includes: receiving, over an electronic network, electronic
publishing content for display online; displaying the received
publishing content on a web page along with one or more user
elements by which one or more users may submit sentiment input or
textual input in relation to the received publishing content or a
subportion of the received publishing content; receiving, from each
of a plurality of users, a user input related to the displayed
publishing content displayed on the web page, the user input
including an identification of a subportion of the displayed
publishing content and a sentiment input or a textual input;
analyzing, for each subportion of the displayed publishing content,
any user input received from each of one or more of the plurality
of users in relation to the subportion; computing, for each
subportion of the displayed publishing content, a sentiment score
based on analysis of the analyzed user inputs received from each of
one or more of the plurality of users in relation to the
subportion; and displaying, for each subportion of the displayed
publishing content, indicia representing the sentiment score
computed for the subportion, along with at least one user element
by which one or more further users are enabled to provide user
input to further modify the computed and indicated sentiment
score.
[0006] According to certain embodiments, systems are disclosed
processing, evaluating, and displaying user input. One system
includes a memory having processor-readable instructions stored
therein; and a processor configured to access the memory and
execute the processor-readable instructions, which when executed by
the processor configures the processor to perform a method. In an
exemplary method, the method includes: receiving, over an
electronic network, electronic publishing content for display
online; displaying the received publishing content on a web page
along with one or more user elements by which one or more users may
submit sentiment input or textual input in relation to the received
publishing content or a subportion of the received publishing
content; receiving, from each of a plurality of users, a user input
related to the displayed publishing content displayed on the web
page, the user input including an identification of a subportion of
the displayed publishing content and a sentiment input or a textual
input; analyzing, for each subportion of the displayed publishing
content, any user input received from each of one or more of the
plurality of users in relation to the subportion; computing, for
each subportion of the displayed publishing content, a sentiment
score based on analysis of the analyzed user inputs received from
each of one or more of the plurality of users in relation to the
subportion; and displaying, for each subportion of the displayed
publishing content, indicia representing the sentiment score
computed for the subportion, along with at least one user element
by which one or more further users are enabled to provide user
input to further modify the computed and indicated sentiment
score.
[0007] According to certain embodiments, a non-transitory computer
readable medium is disclosed as storing instructions that, when
executed by a computer, cause the computer to perform a method, the
method receiving, over an electronic network, electronic publishing
content for display online; displaying the received publishing
content on a web page along with one or more user elements by which
one or more users may submit sentiment input or textual input in
relation to the received publishing content or a subportion of the
received publishing content; receiving, from each of a plurality of
users, a user input related to the displayed publishing content
displayed on the web page, the user input including an
identification of a subportion of the displayed publishing content
and a sentiment input or a textual input; analyzing, for each
subportion of the displayed publishing content, any user input
received from each of one or more of the plurality of users in
relation to the subportion; computing, for each subportion of the
displayed publishing content, a sentiment score based on analysis
of the analyzed user inputs received from each of one or more of
the plurality of users in relation to the subportion; and
displaying, for each subportion of the displayed publishing
content, indicia representing the sentiment score computed for the
subportion, along with at least one user element by which one or
more further users are enabled to provide user input to further
modify the computed and indicated sentiment score.
[0008] Additional objects and advantages of the disclosed
embodiments will be set forth in part in the description that
follows, and in part will be apparent from the description, or may
be learned by practice of the disclosed embodiments. The objects
and advantages of the disclosed embodiments will be realized and
attained by means of the elements and combinations particularly
pointed out in the appended claims.
[0009] It is to be understood that both the foregoing general
description and the following detailed description are exemplary
and explanatory only and are not restrictive of the scope of
disclosed embodiments, as set forth by the claims.
BRIEF DESCRIPTION OF THE DRAWINGS
[0010] The accompanying drawings, which are incorporated in and
constitute a part of this specification, illustrate various
exemplary embodiments and together with the description, serve to
explain the principles of the disclosed embodiments.
[0011] FIG. 1 is a schematic diagram of a network environment for
processing and displaying user input with published content,
according to an embodiment of the present disclosure.
[0012] FIG. 2 is a flow diagram of an exemplary method for
analyzing user input related to subportions of published content
and displaying indicia based on the analysis, according to an
embodiment of the present disclosure.
[0013] FIG. 3 illustrates an exemplary graphical user interface
(GUI) of a web page displaying published electronic content,
according to an embodiment of the present disclosure.
[0014] FIG. 4 illustrates an exemplary GUI of an excerpt of a web
page along with user elements for receiving user input, according
to an embodiment of the present disclosure.
[0015] FIG. 5 illustrates another exemplary GUI of an excerpt of a
web page along with user elements for receiving user input,
according to an embodiment of the present disclosure.
[0016] FIG. 6 illustrates another exemplary GUI of an excerpt of a
web page along with user elements for receiving user input,
according to an embodiment of the present disclosure.
[0017] FIG. 7 illustrates another exemplary GUI of an excerpt of a
web page along with user elements for receiving user input,
according to an embodiment of the present disclosure.
[0018] FIG. 8 illustrates another exemplary GUI of an excerpt of a
web page along with user elements for receiving user input,
according to an embodiment of the present disclosure.
[0019] FIG. 9 is a block diagram of an exemplary computer system in
which embodiments of the present disclosure may be implemented.
DESCRIPTION OF THE EMBODIMENTS
[0020] While the present disclosure is described herein with
reference to illustrative embodiments for particular applications,
it should be understood that embodiments of the present disclosure
are not limited thereto. Other embodiments are possible, and
modifications can be made to the described embodiments within the
spirit and scope of the teachings herein, as they may be applied to
the above-noted field of the present disclosure or to any
additional fields in which such embodiments would be of significant
utility.
[0021] In view of the challenges associated with the conventional
techniques outlined above, systems and methods are disclosed herein
for analyzing and displaying user sentiment and user textual input
adjacent to published electronic content. As described below, these
challenges may be addressed in a number of ways. First, as
described in further detail with respect to FIGS. 3 and 8, user
inputs, e.g., comments, may be analyzed to determine (1) a
sentiment score for the user input based on contextual analysis
and/or other users' sentiments about said comment, (2) which
subportion of a web page said comment is related to and/or (3)
appropriate meta tags ("tags") to assign to said comment. Second,
as described in further detail with respect to FIGS. 4-8, received
user input may be associated with and displayed in spatial relation
to (e.g., adjacent to) particular subportions of the published
electronic content. Using various techniques, as further described
below, each subportion may be assigned appropriate tags and/or a
sentiment score for generating relevant indicia to associate with
the subportion.
[0022] Further, in some embodiments, the challenges described above
may be addressed by providing article-specific/customizable meta
tags and filters that enable the user to provide context to their
comment (e.g. "pro-campaign finance reform," "bad supreme court
decision," "cited references," etc.). In some embodiments, the
challenges described above may be addressed by enabling users to
cite/remark on specific subportions of the content (e.g., targeted
comments "This quoted study was debunked in the NE Journal of
Medicine, see"). Additionally or alternatively, in some
embodiments, the challenges described above may be addressed by
providing users the means to filter and locate comments/commenters
of a particular disposition. The comment meta-data, coupled with
data the user opts to make public (i.e. via their profile tags,
e.g. "Conservative," "Liberal," etc.) provides a more social and
interactive experience.
[0023] User input, as used herein, may include comments or
messages, "likes," "dislikes," etc., submitted by different users,
e.g., as part of an online article, message board, or forum
provided via a web page accessible over the Internet. The different
users may be participants of one or more virtual conversations or
message threads including a series of comments posted by different
users/participants at various times to the online article, message
board, or forum. The comments may be associated with an article or
a blog entry displayed on the web page. Each user may post or
submit user input related to a specific subportion of the article
or blog entry in this example. Subportions may be a section, title,
paragraph, sentence, phrase, fact, word, etc. The user input may be
submitted by each user via an interface provided on a web page that
is loaded within a web browser executable at the user's computing
device. Also, the user input may be anything, including, but not
limited to comments and/or sentiment. Comments may be in the form
of electronic messages including, for example, text, graphics
(e.g., icons or "emoticons"), and/or other types of content (e.g.,
embedded audio or video content). Sentiment may be in the form of
ratings, grades, thumbs up or thumbs down, and/or up votes or down
votes.
[0024] In some embodiments, comments and sentiment may be displayed
in close spatial relation to subportions of electronic publishing
content. Indicia may be associated with each subportion indicating
user sentiment. As will be described in further detail below, a
sentiment score may be calculated for a subportion based on one or
more parameters associated with user input. Examples of such
parameters include, but are not limited to, analysis of textual
input, analysis of sentiment input, analysis of the submitting
user's profile, a demographic of the submitting user, activity
level of the conversation, and/or a number of users providing
content related to the subportion.
[0025] In the detailed description herein, references to "one
embodiment," "an embodiment," "an example embodiment," etc.,
indicate that the embodiment described may include a particular
feature, structure, or characteristic, but every embodiment may not
necessarily include the particular feature, structure, or
characteristic. Moreover, such phrases are not necessarily
referring to the same embodiment. Further, when a particular
feature, structure, or characteristic is described in connection
with an embodiment, it is submitted that it is within the knowledge
of one skilled in the art to effect such feature, structure, or
characteristic in connection with other embodiments whether or not
explicitly described.
[0026] Reference will now be made in detail to the exemplary
embodiments of the disclosure, examples of which are illustrated in
the accompanying drawings. Wherever possible, the same reference
numbers will be used throughout the drawings to refer to the same
or like parts.
[0027] FIG. 1 is a schematic diagram of an exemplary network
environment in which electronic messages and other user input may
be processed and displayed, according to an embodiment of the
present disclosure. As shown in FIG. 1, the environment may include
a plurality of user or commenter devices 102 that are
communicatively coupled to each other as well as a plurality of
server systems 106, a browser web server 114, and/or a mobile web
server 116 via an electronic network 100. Electronic network 100
may include one or a combination of wired and/or wireless
electronic networks. Network 100 may also include a local area
network, a medium area network, or a wide area network, such as the
Internet.
[0028] In one embodiment, each of user or commenter devices 102 may
be any type of computing device configured to send and receive
different types of content and data to and from various computing
devices via network 100. Examples of such a computing device
include, but are not limited to, a desktop computer or workstation,
a laptop computer, a mobile handset, a personal digital assistant
(PDA), a cellular telephone, a network appliance, a camera, a smart
phone, an enhanced general packet radio service (EGPRS) mobile
phone, a media player, a navigation device, a game console, a
set-top box, or any combination of these or other types of
computing devices having at least one processor, a local memory, a
display (e.g., a monitor or touchscreen display), one or more user
input devices, and a network communication interface. The user
input device(s) may include any type or combination of input/output
devices, such as a keyboard, touchpad, mouse, touchscreen, camera,
and/or microphone.
[0029] In one embodiment, each of the user or commenter devices 102
may be configured to execute a web browser or mobile browser
installed for displaying various types of content and data received
from any of server systems 106 and/or web servers 114 and 116 via
network 100. Server systems 106 in turn may be configured to
receive user input, e.g., in the form of comments, from user or
commenter devices 102 over electronic network 100. The comments may
be submitted by a user at each device 102 through an interface
provided on a web page loaded within the browser executable at each
device.
[0030] While browser web server 114 and mobile web server 116 are
shown separately in FIG. 1, it should be noted that web servers 114
and 116 may be implemented using a single server device or system.
In an example, such a single server may be a web server that is
configured to provide different versions of a web page and
associated content to each of user/commenter devices 102 according
to the type of device or web browser executable at the device. The
different versions of the web page may include, for example, a
desktop version and a mobile version, for which the web page
content may be formatted appropriately for display via the
particular type of browser at the device. Further, any of the
devices or functionality of server systems 106, browser web server
114, and/or a mobile web server 116 may be combined together or
separated, and may be operated by a single administrative entity,
or outsourced to one or more other entities, such as a web hosting
entity, web storage entity, and/or cloud computing service,
possibly disposed remotely of each other.
[0031] As shown in the example of FIG. 1, server systems 106 may
include a commenting processor 110. In an embodiment, commenting
processor 110 may be configured to analyze and execute a scoring
algorithm in order to calculate or compute a sentiment score, as
will be described in further detail below. The sentiment score may
reflect, for example, the popularity, importance, feeling, and/or
positivity/negativity of a comment and/or subportion based on the
user input provided with respect to the comment and/or subportion,
as received from user/commenter devices 102.
[0032] Also, as shown in FIG. 1, server systems 106 may include one
or more databases 108. In an embodiment, databases 108 may be any
type of data store or recording medium that may be used to store
any type of data including, for example, user input (e.g., comment,
sentiment, etc.) as well as the scoring algorithm used to score
such content. In an embodiment, commenting processor 110 may be
configured to receive user input from user/commenter devices 102
and store the received content within databases 108. In some
implementations, any received data may be stored in the databases
108 in an encrypted form to increase security of the data against
unauthorized access.
[0033] In a further embodiment, commenting processor 110 may be
configured to process the user input using the scoring algorithm.
In some embodiments, sentiment scores are calculated for a user
input, for a relevant subportion, or for both. For example, in some
embodiments, the scoring algorithm determines the sentiment by
calculating a sentiment score for the user input. Additionally or
alternatively, sentiment expressed within user input may be used to
calculate a sentiment score for the subportion to which the user
input relates. Further, in some embodiments, the sentiment scores
calculated for user input may factor into the scoring algorithm for
the subportion for which they relate. For example, a subportion may
have several comments related to it. A sentiment score may be
determined based on an analysis of these comments so a user can see
how other users feel about said subportion. It may be beneficial
for the user to, additionally or alternatively, see other user
opinions on these comments. For example, one comment may be a spam
advertisement and thus receive low ratings from other users,
thereby resulting in a low sentiment score. This comment may be
highlighted in red and, as described with respect to FIG. 8, since
comments with low scores may be filtered, it might not be displayed
to the user at all. In some embodiments, the sentiment score of the
comment may then be used in the scoring algorithm for the
subportion. For example, the sentiment expressed within a comment
with a low sentiment score (e.g., a comment that received low
ratings from other users) may be given less weight in the scoring
algorithm for calculating the sentiment score of the related
subportion.
[0034] In a further example, commenting processor 110 may use the
scoring algorithm to compute a sentiment score for each user
comment and/or subportion within a web page or online message board
or forum included within the web page. As described above, each
subportion may have elicited one or more sentiments and/or comments
posted or submitted by different users of the message board or
forum within the web page, as displayed at each user's device
(e.g., each of user/commenter devices 102). The computed sentiment
score for each user input may be assigned to the subportion and
used to calculate an overall sentiment score for that subportion.
Indicia based on the received input and/or computed overall
sentiment score may be displayed relative to the subportion. As
described above, the sentiment score computed for each subportion
may reflect a level of popularity, agreement, importance, feeling,
and/or positivity/negativity, which may be determined based on
various parameters associated with the sentiment, comment,
individual participants, and/or users/commenters providing
user-generated content related to the subportion. Accordingly, the
subportions may be scored such that subportions determined to be
relatively more agreeable, popular, important, and/or
positive/negative are given relatively high sentiment scores, and
may be, for example, associated with indicia identifying relative
agreeableness, popularity, importance, and/or
positivity/negativity.
[0035] Server systems 106 may also include a commenting user
interface (UI) module 112 that facilitates receiving user input
from users and displaying the received user input. The displayed
content may include, for example, user input that has been
processed or scored along with the subportion to which it relates,
as described above. For example, commenting UI module 112 may be
configured to generate, render, and transmit web page content
including an article or blog entry. Such web page content may be
divided into subportions. Displayed within the webpage may be one
or more message streams of comments posted by users related to some
or all subportions. Thus, the web page content may include user
input in the form of comments/sentiment. The user input may include
displaying, for example, any one or combination of text, images,
sentiment (e.g., icons for users to "like" or "pin" their favorite
subportions or comments, etc.) to user/commenter devices 102 via
network 100. Additional features and characteristics of the
commenting and scoring functionality of commenting processor 110
will be described in further detail below with respect to the
exemplary graphical user interfaces (GUIs) of comments and
sentiments associated with subportions of a web illustrated in
FIGS. 3-8.
[0036] FIG. 2 is a flow diagram of method 200 for changing and
displaying a sentiment score indicating the user sentiment for a
subportion of received electronic publishing content of a web page,
according to an embodiment of the present disclosure. It should be
noted that, although this exemplary method describes sentiment
scores for subportions of a web page, this method may be applied to
user comments to identify a sentiment score, display indicia,
and/or tag a user comment or comment conversation. The method may
involve algorithmically computing a sentiment score for each
subportion. For example, the score may be a function of a number of
factors, which may be represented as a combination of variables for
a scoring formula. The score may be updated periodically or as
desired by adjusting a value of each variable within the formula.
In an embodiment, the score may be updated dynamically in response
to detecting or receiving an indication of a new user action with
respect to a subportion or a comment on the subportion. Such a new
user action may include, for example, the addition of user input
(e.g., a new comment, a new "thumbs up") related to a subportion of
the electronic content. The user input may be received from a user
or user device (e.g., any of user/commenter devices 102 of FIG. 1,
as described above) via a communication network (e.g., network 100
of FIG. 1, as described above).
[0037] As shown in FIG. 2, method 200 may include steps 202, 204,
206, 208, 210, 212, 214, 216, and 218. However, it should be noted
that method 200 may include more or fewer steps as desired for a
particular implementation. In an example, one or more of the
above-listed steps of method 200 may be executed by server systems
106, browser web server 114, and/or mobile web server 116 of FIG.
1, as described above. However, method 200 is not intended to be
limited thereto, and the steps of method 200 may be performed by
any server or other type of computing device having at least one
processor, a memory, and a network communication interface for
sending and receiving information from one or more user
devices.
[0038] As shown in FIG. 2, method 200 may include receiving
electronic publishing content for display online (step 202). Method
200 may also include dividing the received content into a plurality
of subportions (step 204). In some examples, the electronic content
for display online may be an article or blog entry. In some
embodiments, the received content may be divided into letters,
words, phrases, sentences, paragraphs, and/or sections. In some
embodiments, step 204 may not be performed initially, and instead,
subportions may be created once a user/users select a portion of
the electronic content for comment or sentiment. For example, a
user may highlight a phrase he/she wishes to comment on and then
this highlighted portion may be designated as a subportion.
[0039] In step 206, a server, e.g., browser web server 114 and/or
mobile web server 116 of FIG. 1, may generate and display the
received content on a web page. In some embodiments, the indicia
distinguishing subportions may be displayed during step 206 as
well. Once the received content is displayed on the web page, a
user may be able to provide input (e.g., comments or sentiments)
related to subportions of the web page. In step 208, a server may
receive such user input on at least one of the subportions. The
user input may be any type of input. The user input may also
include an identification and/or designation of a user-specific
subportion of the electronic publishing electronic publishing
content. For example, a user may select some words or sentences,
may select and drag, may highlight, etc. User input may be received
from a user/commenter device 102 over the Internet.
[0040] FIG. 2 reflects that the received user input may include
sentiment input and/or textual input, but this disclosure is not
limited thereto. In some embodiments, if a sentiment input was
received in step 208, method 200 may proceed to step 210. Sentiment
input may include receiving from one user/commenter device 102 a
"rating," a "like," a "favorite," a "block," an "up vote," a
"thumbs down," or any other action for expressing sentiment. The
received sentiment input may be analyzed (step 210). In some
embodiments, the analysis may include determining whether the
sentiment is positive or negative. For example, in some
embodiments, a thumbs up or thumbs down icon may be available for
sentiment input. If a user selects the thumbs up icon, an analysis
may determine that this is a positive input. In some examples,
indicia of this sentiment may be displayed. There may be a count of
each thumbs up or thumbs down. If the current display shows 58
thumbs up and 43 thumbs down and user selects thumbs down, the
display may update to 58 thumbs up and 44 thumbs down. In one
embodiment, sentiment may be a sliding scale of 1-5, the Liked
scale, etc. Once the received sentiment input has been analyzed,
method 200 may proceed to step 216.
[0041] If, in step 208, the received user input is textual input
(e.g. a comment) related to the at least one subportion of the web
page, method 200 may proceed to 212. In step 212, the received
textual input may be displayed in relation to the subportion. For
example, as shown in FIG. 4, the user's textual input related to
subportion 304 may be displayed in comment box 422. Method 200 may
then proceed to step 214 or, in some embodiments, method 200 may
skip step 212 and proceed to step 214 after receiving user textual
input in step 208.
[0042] In step 214, method 200 may include analyzing the text for
sentiment. In some embodiments, a keyword search may be performed
to determine sentiment. For example, if a negative word (e.g.,
"disagree") is detected within the textual input, the analysis may
determine the sentiment of the textual input is negative. If strong
sentiment terms or words (e.g., "love") are detected, the analysis
may determine the sentiment of the textual input is highly positive
or negative. Similarly, if there are multiple positive terms within
the textual input, the analysis may determine the sentiment of the
textual input is highly positive. Other analysis of the textual
input may also include length, punctuation, etc.
[0043] In some embodiments, the user's action history and/or user's
profile may, additionally or alternatively, be analyzed in step
214. The sentiment of a user's textual input and/or appropriate
tags for said input may be based on a user's profile or history by
default. For example, if the user identifies as a liberal in
his/her profile, textual input related to a subportion praising
conservatives may, by default, be analyzed as being a negative
sentiment. Similarly, if a user's history shows repeated negative
textual input when an article, comment, and/or subportion praise
liberals, all comments on subportions praising liberals may, by
default be analyzed as containing a negative sentiment. In some
embodiments, a user may wish to hide words like "liberal" and
"conservative" from being pulled from their profiles to analyze
comments.
[0044] Other examples of relevant statistics that may be used
during the analysis of the textual input may include, but are not
limited to, the number of comments received (e.g., during a
predetermined period of time), the time-of-day when the comments
are received, and parameters (e.g., geographic location,
noteworthiness or popularity, commenting frequency, etc.) of the
users from which comments are received. In an embodiment, each user
may be associated with a popularity index or rating. The popularity
rating of a user may be based on, for example, the number of other
users who may be listed as "fans" or "followers" of the user.
Additionally or alternatively, the popularity rating may be based
on the number of "likes" or number of times that other users have
marked a comment posted by the user as a favorite or otherwise
indicated their approval of the user's comments. Other users may
indicate themselves to be fans of the user or mark a comment by the
user as a favorite by selecting a user interface control element
provided via, for example, a GUI for displaying conversations and
user-submitted comments associated with an online message board or
forum.
[0045] In some embodiments, textual input may also be analyzed for
appropriate tags. Analyzing comments for appropriate tags will be
described in further detail below.
[0046] After completion of step 214, method 200 may proceed to step
216. In step 216, a sentiment score associated with the at least
one subportion may be modified. This modification may be based on
the analysis in step 210 of the received sentiment input and/or the
analysis in step 214 of the received textual input. In some
embodiments, a sentiment score may be initially set at a neutral
position (for example, 0 in a scale from -5 to +5, or 2.5 out of 5
stars) and each time a user provides feedback/sentiment regarding
that subportion, the sentiment score may be adjusted. After
modifying the sentiment score associated with the at least one
subportion, method 200 may proceed to step 218. In step 218, a
server may change user sentiment indicia of the at least one
subportion based on the modified sentiment score. In some
embodiments, if the sentiment score was decreased due to negative
sentiment input or textual input, a box encompassing the at least
one subportion may turn from dark green to light green or a set of
stars may go from 3.8 to 3.75 stars.
[0047] FIG. 3 illustrates an exemplary GUI for displaying received
electronic content on a web page. Specifically, FIG. 3 depicts an
entire article, "Changing Political Landscapes," published on a web
page. In the embodiment illustrated in FIG. 3, title 2 is displayed
above a "Show Sentiment" icon 4 and "Hide Sentiment" icon 6. The
body of the article is displayed below "Show Sentiment" icon 4 and
"Hide Sentiment" icon 6, although these icons could be shown
anywhere on the web page. In this embodiment, the body of the
article may be divided into subportions, each subportion
corresponding to a paragraph. For example, the article displayed in
FIG. 3 may be divided into subportions 302, 304, 306, 308, 310,
312, and 314.
[0048] An overall comment box 316 for commenting on the article as
a whole may displayed below the body of the article. In some
embodiments, a user may provide textual input (e.g., a comment)
within overall comment box 316. In such a case, the user may not be
targeting any particular subportion of the web page to provide
sentiment for. In some embodiments, an analysis may be performed on
the user's textual input within the overall comment box 316. For
example, if the user quotes a section of the article, (e.g.
"SIXTY-FOUR PERCENT OF AMERICANS VIEW THE REPUBLICAN PARTY
UNFAVORABLY" from subportion 304) an analysis may determine the
user is providing sentiment related to subportion 304. This comment
may then be assigned a tag associating it with subportion 304. In
some embodiments, a direct quote may not be necessary and common
keywords may be used to associate comments with a particular
subsection. For example, if textual input is entered into the
overall comment box 316 that contains the word "Boehner," this
comment may be associated with subportion 308, since it is the only
subportion that mentions John Boehner. In some embodiments, if
comments directed to a particular subportion are displayed, textual
input to the overall comment box 316 with a tag assigning it to
that subportion may also be displayed.
[0049] In some embodiments, the textual input into the overall
comment box 316 may also be analyzed for sentiment. If negative
words like "lie," "disagree," "false," etc. appear within the
comment, the sentiment score associated with the comment and/or
subportion 304 may be decreased. Similarly, the user's history
and/or profile may be analyzed. If the user identifies himself as a
Republican, the assumption may be made that the user does not like
a subportion describing the low ratings of the Republican Party.
The sentiment score for subportion 304 may thus be decreased. If
the user's history includes many positive comments or sentiments
for quotes, articles, subportions, etc. that describe low ratings
for the Republican Party, it may be assumed this comment is also
positive. The sentiment score for subportion 304 may thus be
increased based on this user history.
[0050] FIG. 4 illustrates an excerpt of the electronic content. In
this figure, the excerpt is the body of the article. A user may
highlight a portion of text within the electronic content, e.g.,
"IT'S ONLY A 2-POINT INCREASE FROM A SURVEY TAKEN SEPT. 27 THROUGH
29" of subportion 304. When a user selects a subportion or
highlights text within a subportion, a comment box, e.g. comment
box 422, may be displayed proximate to subportion 304. In the
example illustrated in FIG. 4, if the user selects text within
subportion 304, comment box 422 may be displayed under subportion
304 and the user may insert textual input within comment box 422.
Display of user textual input is described below with respect to
FIG. 8.
[0051] In some embodiments, the user's textual input may be
categorized or assigned tag. For example, a server may auto-suggest
tags relevant to the textual input (e.g., if the user quotes
something, the server may assign a tag related to the quote.) The
server may automatically tag a comment by default. For example, if
the comment recites a quote from the text about a particular
politician, e.g., John Boehner, the comment and/or subsection may
automatically be tagged with a tag entitled "John Boehner." In some
embodiments, the user who submitted the comment or other users
reading the comment may un-tag irrelevant/incorrect tags. In some
embodiments, the user may create tags for his/her own comments.
Additionally or alternatively, other users may assign tags to a
comment.
[0052] In some embodiments, tags may be automatically associated
with one another. For example, if one quote is subject to many
comments, many of which are commonly associated with two tags, the
two tags may automatically be associated with one another by the
system. If a subsequent user sorts or selectively displays the
comments by selecting the first tag, the second tag may
additionally be suggested by the system for display and/or sorting
purposes.
[0053] In some embodiments, candidate tags may be created based
upon the comment. The confidence in these candidate tags may be
increased in response to analyzing the user's profile and prior
comments. For example, political persuasion, religious persuasion,
etc., may be tags gleaned from the comment, other comments the user
has made, and/or the user's profile. For example, the comment may
cause the automatic creation of a candidate tag "liberal." However,
upon review of the candidate's profile and previous comments, the
tag of "liberal" may be discarded. Another tag, for example,
"libertarian," may also be automatically chosen. A tag may also
simply be the username, which would allow other users to search for
comments made by that user.
[0054] FIG. 5 illustrates another embodiment of an excerpt of the
electronic content. Specifically, FIG. 5 depicts a view of the body
of an article once a user selects the "Show Sentiment" icon 4. It
should be noted that in some embodiments, a web page may initially
be displayed with indicia of sentiment for each subportion without
user interaction with show sentiment icon 4.
[0055] A user may provide sentiment input for each subportion of
the article. In the embodiment illustrated in FIG. 5, a user may
provide sentiment input by selecting the up vote icon 32 or the
down vote icon 34. A user may provide textual input by, as
described with respect to FIG. 4, selecting text within a
subportion or selecting any point within the subportion. Such
actions may cause a comment box to appear. In some embodiments,
selecting the comment point icon 36 may cause a comment box to
appear to receive textual input from the user. Additionally or
alternatively, selecting the comment point icon 36 may display
previous user comments, as further described with respect to FIG. 8
below. As shown in FIGS. 5-8, each of subportions 502, 504, 506,
508, 510, 512, and 514 may be associated with a way of providing
sentiment input and/or textual input. The up/down vote, comment
boxes, and configuration of the GUI are merely exemplary.
[0056] In the embodiment illustrated in FIG. 5, each of subportions
502, 504, 506, 508, 510, 512, and 514 may have indicia based on its
sentiment score. As shown in FIG. 5, these indicia may include
shading and/or coloration, each shading/coloration indicating a
sentiment score or a range of sentiment scores. The indicia may be
any indication that expresses a range of sentiment scores, for
example, various colors, number of stars, percentages, etc. In some
embodiments, for example, a range of colors from green to red may
encompass each subportion. A green box may encompass a subportion
that may have a high or very positive sentiment score. Whereas a
dark red box may encompass a subportion that may have a very
negative sentiment score. As described in FIG. 2, a very negative
sentiment score may be due to, for example, multiple negative
sentiment input (e.g., many down votes), strong negative sentiment
input (e.g., 2% out of 100%), and/or negative textual input (e.g.,
multiple comments including negative words like "hate," "strongly
disagree," "incorrect," etc.).
[0057] FIG. 6 illustrates another embodiment of an excerpt of the
electronic content. Specifically, FIG. 6 depicts a view of the body
of an article when both indicia of sentiment and a comment box 62
are displayed to the user. In some embodiments, a comment box may
be initially displayed for each subportion without user
interaction. In some embodiments, if a user indicates a desire to
comment on a specific subportion (e.g., by selecting a subportion
502, highlighting text with subportion 502, or selecting comment
point icon 36) comment box 62 may be displayed proximate to said
subportion.
[0058] In some embodiments, a user may make several comments about
a single subportion. For example, as illustrated in FIG. 7, a user
may make multiple comments with respect to subportion 502. Display
of each of comment boxes 72, 74, and 76 may be initiated in a
different way. For example, the user may have selected comment
point icon 36 to initiate display of comment box 76, allowing the
user to add textual input related to subportion 502. Additionally
or alternatively, the user may click/select any point within
subportion 502 to initiate display of comment box 74, allowing the
user to add textual input related to subportion 502. In some
embodiments, the user may highlight a specific section of the
subportion 502. As shown in FIG. 7, the user may highlight the term
"THE REPUBLICAN PARTY" to initiate display of the comment box 72
may be displayed, allowing the user to input text related to "THE
REPUBLICAN PARTY," and not the entirety of subportion 502.
[0059] In some embodiments, the ability to provide sentiment (e.g.
sentiment input or textual input) related to individual words or
phrases within a paragraph (e.g., "THE REPUBLICAN PARTY"), may be
used to calculate a sentiment score for the phrase, separate from
the full paragraph or subportion. For example, subportion 508 of
FIG. 7 is marked with first indicia. In FIG. 7, the first indicia
may include a first shading encompassing subportion 508. The phrase
"42 PERCENT FROM 39 PERCENT" may have second indicia (e.g., second
shading). This second shading may indicate that the phrase "42
PERCENT FROM 39 PERCENT" may have a different sentiment score
associated with it than the remaining portions of subportion
508.
[0060] In some embodiments, a user may select an indicator (e.g.
click a shaded portion encompassing a subportion). The input of
other users may then be displayed to show how/why the subportion is
designated with that indicator. For example, sentiment scores,
number of comments/votes or the actual previous use comments may be
displayed.
[0061] FIG. 8 illustrates another embodiment of an excerpt of the
electronic content. Specifically, FIG. 8 depicts a view of the body
of an article when both indicia of user sentiment for a plurality
of subsections and previous user comments 32, 34, and 36 are
displayed to the user. These comments may be displayed proximate
the subportion to which they relate. Previous user comments 32, 34,
and 36 may have been submitted by any user, including the user
currently viewing the web page. The previous comments may be in any
order and displayed in any configuration.
[0062] It may be determined which subportion they relate to by
tagging them when a user selected the subportion or terms within
the subportion as described in FIG. 2-7. Additionally or
alternatively, comments submitted in overall comment box 316 may be
tagged to relate to a specific subportion and thus displayed
proximate to that subportion. These comments may be determined to
be related to a subportion by analysis of the text, the submitting
user's tags, and/or other users' tags of the comment.
[0063] In some embodiments, previous user comments related to
subportions may be displayed initially, without user action. In
some embodiments, previous user comments related to subportions may
not be displayed until some user action is taken. For example, a
user may select the comment point icon 36. In some embodiments,
previous user comments may be displayed when a user "hovers" or
"mouse" over a particular quote or portion of the text. This
"hovering" action may result in comments previously tagged as
relevant to the text to automatically pop up over the text. These
previously tagged comments may be sorted by default by popularity,
time made, ideological similarity with the user, etc.
[0064] In some embodiments, previous user comments may be filtered.
The user currently viewing the web page may select a filter. In
some embodiments, the web page administer, content provider, etc.
may choose to filter which comments are displayed.
[0065] In some embodiments, previous user comments may be filtered
by user sentiment. Users may provide sentiment (e.g. sentiment
input, textual input, etc.) with respect to previous user comments.
In such embodiments, a sentiment score may be calculated for each
comment as well. This calculation may be performed in a manner
similar to that described with respect to web page subportions of
FIG. 2. In some embodiments, a user or a web page administrator may
filter all comments with less than three stars, thus only
displaying comments with a sentiment score of 3 or more stars, for
example.
[0066] In some embodiments, tags may be used to filter comments.
Comments may be filtered by these tags. A user or content provider
may select that only comments associated with certain tags be
displayed. The selection may be done by the user typing the desired
tag. For example, a user may type in a username if the user wants
to see all comments by a specific user. A user may type "liberal"
to see all comments tagged as being made by a liberal user.
[0067] A user may select a "show me similar comments" icon to
automatically search for comments with a similar set of tags,
comments related to the same or similar quoted portion of the
content, and/or comments from users with a similar level of respect
(e.g., users with a large number of up votes per comment).
[0068] In some embodiments, comments may be sorted by user respect.
This may be determined by, for example, the average number of up
votes per comment that the user has made. User respect may also be
sorted by the ratio of up votes to down votes. A higher ratio of up
votes to down votes in a user's comment history may be a better
indicator of comment quality than the sheer number of up votes.
[0069] A user may set all of these comment preferences by default.
For example, a user may set rules such that only user accounts
associated with a "liberal" or "moderate" tag be displayed in the
comments section. A user may also set a rule that only users with a
user respect above a predetermined level be displayed. Multiple
rules may also be combined and/or prioritized. A plurality of rules
and a hierarchy of sorting priorities may also be designated for
each piece of content and/or by default. For example, a user may
designate that only comments associated with a "conservative" tag
be displayed, sorted primarily by date, and secondarily by user
respect. These rules may be set by default for all content
[0070] In some embodiments, filter rules may be automatically
created. For example, a user's comments and interactions may be
monitored. For example, a server may monitor the tags associated
with comments for which the user provides sentiment input (e.g., up
votes and down votes), provides textual input (e.g., comments on),
or otherwise interacts with. Rules may automatically be created for
comment display based upon these interactions. For example, if a
user tends to up vote comments which are associated with a
"liberal" tag and a high level of user respect, then an automatic
rule may be created which displays content to the user matching
these tags.
[0071] In some embodiments, comments may automatically be
associated with other comments quoting the same or similar portions
of the content. There may be a predetermined proximity threshold
for two comments to be considered related. For example, a first
comment may quote or tag "four score" and a second comment may
quote or tag "and seven years ago" from a passage in content that
reads "four score and seven years ago." Since the two comments
concern adjoining text, they may be associated with each other as
being within a predetermined proximity threshold.
[0072] Similarly, in some embodiments, tag associations may also be
based on grammar and punctuation. For example, comments that cite
"four score" may be associated with comments that cite "seven years
ago" because both portions of the content come from the same
sentence. Alternatively or in addition, comments may be associated
with each other and tagged accordingly if they are on the same side
of a comma, hyphen, semi-colon, or any other manner of associating
comments by grammar and punctuation. Two portions of a content
piece may be given confidence scores based on multiple criteria,
with a confidence above a predetermined threshold causing two
comments to become associated with each other. For example, a
confidence score that two comments are related may be increased
based upon shared words in the comments themselves, proximity of
the quoted content pieces to each other, whether the quotes overlap
or are in the same sentence, etc.
[0073] Additional objects and advantages of the disclosed
embodiments will be set forth in part in the description that
follows, and in part will be apparent from the description, or may
be learned by practice of the disclosed embodiments. The objects
and advantages of the disclosed embodiments will be realized and
attained by means of the elements and combinations particularly
pointed out in the appended claims.
[0074] The examples described above with respect to FIGS. 1-8, or
any part(s) or function(s) thereof, may be implemented using
hardware, software modules, firmware, tangible computer readable
media having instructions stored thereon, or a combination thereof
and may be implemented in one or more computer systems or other
processing systems.
[0075] FIG. 9 illustrates a high-level functional block diagram of
an exemplary computer system 700, in which embodiments of the
present disclosure, or portions thereof, may be implemented, e.g.,
as computer-readable code. For example, each of the exemplary
devices and systems described above with respect to FIGS. 1-8 can
be implemented in computer system 700 using hardware, software,
firmware, tangible computer readable media having instructions
stored thereon, or a combination thereof and may be implemented in
one or more computer systems or other processing systems. Hardware,
software, or any combination of such may embody any of the modules
and components in FIG. 1, as described above.
[0076] If programmable logic is used, such logic may execute on a
commercially available processing platform or a special purpose
device. One of ordinary skill in the art may appreciate that
embodiments of the disclosed subject matter can be practiced with
various computer system configurations, including multi-core
multiprocessor systems, minicomputers, mainframe computers,
computer linked or clustered with distributed functions, as well as
pervasive or miniature computers that may be embedded into
virtually any device.
[0077] For instance, at least one processor device and a memory may
be used to implement the above described embodiments. A processor
device may be a single processor, a plurality of processors, or
combinations thereof. Processor devices may have one or more
processor "cores."
[0078] Various embodiments of the present disclosure, as described
above in the examples of FIGS. 1-8 may be implemented using
computer system 700. After reading this description, it will become
apparent to a person skilled in the relevant art how to implement
embodiments of the present disclosure using other computer systems
and/or computer architectures. Although operations may be described
as a sequential process, some of the operations may in fact be
performed in parallel, concurrently, and/or in a distributed
environment, and with program code stored locally or remotely for
access by single or multi-processor machines. In addition, in some
embodiments the order of operations may be rearranged without
departing from the spirit of the disclosed subject matter.
[0079] As shown in FIG. 9, computer system 700 includes a central
processing unit (CPU) 720. CPU 720 may be any type of processor
device including, for example, any type of special purpose or a
general purpose microprocessor device. As will be appreciated by
persons skilled in the relevant art, CPU 720 also may be a single
processor in a multi-core/multiprocessor system, such system
operating alone, or in a cluster of computing devices operating in
a cluster or server farm. CPU 720 is connected to a data
communication infrastructure 710, for example, a bus, message
queue, network, or multi-core message-passing scheme.
[0080] Computer system 700 also includes a main memory 740, for
example, random access memory (RAM), and may also include a
secondary memory 730. Secondary memory 730, e.g., a read-only
memory (ROM), may be, for example, a hard disk drive or a removable
storage drive. Such a removable storage drive may comprise, for
example, a floppy disk drive, a magnetic tape drive, an optical
disk drive, a flash memory, or the like. The removable storage
drive in this example reads from and/or writes to a removable
storage unit in a well-known manner. The removable storage unit may
comprise a floppy disk, magnetic tape, optical disk, etc. which is
read by and written to by the removable storage drive. As will be
appreciated by persons skilled in the relevant art, such a
removable storage unit generally includes a computer usable storage
medium having stored therein computer software and/or data.
[0081] In alternative implementations, secondary memory 730 may
include other similar means for allowing computer programs or other
instructions to be loaded into computer system 700. Examples of
such means may include a program cartridge and cartridge interface
(such as that found in video game devices), a removable memory chip
(such as an EPROM, or PROM) and associated socket, and other
removable storage units and interfaces, which allow software and
data to be transferred from a removable storage unit to computer
system 700. Control system 700 may receive programming and data via
network communications 970.
[0082] Computer system 700 may also include a communications
interface ("COM") 760. Communications interface 760 allows software
and data to be transferred between computer system 700 and external
devices. Communications interface 760 may include a modem, a
network interface (such as an Ethernet card), a communications
port, a PCMCIA slot and card, or the like. Software and data
transferred via communications interface 760 may be in the form of
signals, which may be electronic, electromagnetic, optical, or
other signals capable of being received by communications interface
760. These signals may be provided to communications interface 760
via a communications path of computer system 700, which may be
implemented using, for example, wire or cable, fiber optics, a
phone line, a cellular phone link, an RF link or other
communications channels.
[0083] The hardware elements, operating systems and programming
languages of such equipment are conventional in nature, and it is
presumed that those skilled in the art are adequately familiar
therewith. Computer system 700 also may include input and output
ports 750 to connect with input and output devices such as
keyboards, mice, touchscreens, monitors, displays, etc. Of course,
the various server functions may be implemented in a distributed
fashion on a number of similar platforms, to distribute the
processing load. Alternatively, the servers may be implemented by
appropriate programming of one computer hardware platform.
[0084] Program aspects of the technology may be thought of as
"products" or "articles of manufacture" typically in the form of
executable code and/or associated data that is carried on or
embodied in a type of machine readable medium. "Storage" type media
include any or all of the tangible memory of the computers,
processors or the like, or associated modules thereof, such as
various semiconductor memories, tape drives, disk drives and the
like, which may provide non-transitory storage at any time for the
software programming. All or portions of the software may at times
be communicated through the Internet or various other
telecommunication networks. Such communications, for example, may
enable loading of the software from one computer or processor into
another, for example, from a management server or host computer of
the mobile communication network into the computer platform of a
server and/or from a server to the mobile device. Thus, another
type of media that may bear the software elements includes optical,
electrical and electromagnetic waves, such as used across physical
interfaces between local devices, through wired and optical
landline networks and over various air-links. The physical elements
that carry such waves, such as wired or wireless links, optical
links or the like, also may be considered as media bearing the
software. As used herein, unless restricted to non-transitory,
tangible "storage" media, terms such as computer or machine
"readable medium" refer to any medium that participates in
providing instructions to a processor for execution.
[0085] It would also be apparent to one of skill in the relevant
art that the present disclosure, as described herein, can be
implemented in many different embodiments of software, hardware,
firmware, and/or the entities illustrated in the figures. Any
actual software code with the specialized control of hardware to
implement embodiments is not limiting of the detailed description.
Thus, the operational behavior of embodiments will be described
with the understanding that modifications and variations of the
embodiments are possible, given the level of detail presented
herein.
[0086] It is to be understood that both the foregoing general
description and the following detailed description are exemplary
and explanatory only and are not restrictive of the disclosed
embodiments, as claimed.
[0087] Other embodiments of the disclosure will be apparent to
those skilled in the art from consideration of the specification
and practice of the invention disclosed herein. It is intended that
the specification and examples be considered as exemplary only,
with a true scope and spirit of the invention being indicated by
the following claims.
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